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IC 8834 



Bureau of Mines Information Circular/1980 






The Impact of U.S. Railroad 
Abandonment on Domestic 
Mineral Industries 

By Ronald F . Balazik 




UNITED STATES DEPARTMENT OF THE INTERIOR 



l[;'ikr> 






Information Circular 8834 

The Impact of U.S. Railroad 
Abandonment on Domestic 
Mineral Industries 

By Ronald F. Balazik 




UNITED STATES DEPARTMENT OF THE INTERIOR 
Cecil D. Andrus, Secretary 

BUREAU OF MINES 

Lindsay D. Norman, Director 



As the Nation's principal conservation agency, the Department of the Interior 
has responsibility for most of our nationally owned public lands and natural 
resources. This includes fostering the wisest use of our land and water re- 
sources, protecting our fish and wildlife, preserving the environmental and 
cultural values of our national parks and historical places, and providing for 
the enjoyment of life through outdoor recreation. The Department assesses 
our energy and mineral resources and works to assure that their development is 
in the best interests of all our people. The Department also has a major re- 
sponsibility for American Indian reservation communities and for people who 
live in Island Territories under U.S. administration. 



v 







X 






This publication has been cataloged as follows: 



Balazik, Ronald F 

The impact of U.S. railroad abandonment on domestic min- 
eral industries. 

(Information circular - Bureau of Mines ; 8834) 

Bibliography: p. 14*16. 

Supt. of Docs, no.: I 28.27:8834. 

1. Mineral industries— United States. 2. Railroads — United States- 
Abandonment. 3. Railroads and state— United States. I. Title. II. 
Series: United States. Bureau of Mines. Information circular ; 8834. 

"TN23&JJ4 [HD9506.U62] 622s [338.2'0973] 80-607948 



For sale by the Superintendent of Documents, U.S. Government Printing Office 
Washington, D.C. 20402 



Jo 

CONTENTS 
^ Page 



3^ 



Oo 



CO 



Abstract 1 

Introduction 1 

Problem background . 1 

Related studies 4 

Study methodology 4 

Data description and analysis 7 

Near-term impact data 7 

Long-range impact data and statistical tests 8 

Long-range impact data 8 

Statistical tests 11 

Cone lus ions 12 

Bibliography 14 

Appendix. — Details of statistical tests 17 

ILLUSTRATION 

1. Schematic diagram showing procedure for mapping abandonment 

impact areas 6 

TABLES 

1. Characteristics of prospective rail line abandonments as of 1978.... 3 

2. Raw and processed mineral materials carried by 52 rail lines 

pending abandonment as of 1978 7 

3. MILS mineral sites within abandonment impact areas, by State 9 



la 



THE IMPACT OF U.S. RAILROAD ABANDONMENT ON DOMESTIC 

MINERAL INDUSTRIES 

by 

Ronald F. Balazik 1 



ABSTRACT 

This Bureau of Mines study is intended to identify and evaluate poten- 
tial effects of impending large-scale U.S. rail line closings (abandonment) 
on domestic nonfuel mineral industries. This is the first nationwide study of 
rail abandonment impacts focused on nonfuel minerals. The analysis presented 
is based principally on a survey of 200 rail freight records and on statis- 
tical tests that correlated 2,000 points in the Bureau's Mineral Industry 
Location System (MILS) with 700 prospective abandonments throughout the 
United States. The conclusions derived from the analysis can be useful 
in evaluating proposed national rail abandonment policy and legislation 
regarding nonfuel mineral shipping. Among these conclusions are the 
following: (1) Certain mineral materials (especially fertilizers) are 
likely to account for a large percentage of the rail traffic affected by 
abandonment in the next few years , but the total tonnage involved will be 
small; (2) abandonment will adversely affect some mineral shippers, partic- 
ularly local short haulers; and (3 abandonment could significantly reduce 
the opportunity to develop new resources or reopen defunct mining facilities. 
Despite these problems, however, the data examined in this study do not 
indicate that current abandonment trends will cause widespread disruption of 
domestic nonfuel mineral shipping. 

INTRODUCTION 

Problem Background 

Considerable interdependence exists between rail transport and mineral 
shipping in the United States. Raw and processed nonfuel mineral materials 
account for approximately one-third of U.S. rail freight tonnage and almost 
one-fifth of rail company gross freight revenues. Railroads, in turn, are 
significant to the U.S. minerals industry. For example, when measured in 
ton-miles , domestic railroads account for the transport of about 25 percent 
of ferrous ores , 90 percent of nonferrous ores , 40 percent of nonmetallic 



■•■Minerals transportation specialist, Branch of Economic Analysis, Bureau of 
of Mines, Washington, D.C. 



minerals, 50 percent of iron and steel, 75 percent of primary nonferrous 
metal products, and 65 percent of stone, clay, and glass products (25) . 2 

In recent years, U.S. rail shipments including mineral freight have 
been subjected to increased rail line closings throughout the country. This 
termination of service (hereafter referred to as "abandonment") is becoming 
a more frequent means of reducing revenue losses by domestic railroad 
companies. In 1976, the Railroad Revitalization and Regulatory Reform Act 
authorized procedures whereby abandonment would be expedited by the Inter- 
state Commerce Commission (ICC). 3 In 1979, legislative proposals that 
include provisions to further expedite abandonment were submitted to Congress 
Apropos of these developments, the Chicago, Milwaukee, St. Paul, and Pacific 
Railroad applied in 1979 for the abandonment of 2,500 miles of track, the 
largest single abandonment in railroad history. 

In September 1977, the ICC announced the prospective abandonment of 
907 rail lines totaling over 20,000 miles of track. Subsequently, in March 
1978, these abandonments were reduced to 688 lines totaling 16,516 miles of 
track, or over 8 percent ©f all U.S. rail trackage. At the current pace of 
ICC abandonment proceedings , all of these lines are certain to be abandoned 
by 1985. The Association of American Railroads predicted that as much as 
40,000 miles of track, equivalent to 20 percent of U.S. trackage, eventually 
would be abandoned (24) . 

The prospective abandonments announced by ICC in 1978 range in length 
from less than 1 mile to nearly 300 miles, but have an average length of 
about 25 miles (table 1). These abandonments are located in 45 States and 
the District of Columbia. More than 30 railroad companies own and operate 
these lines. A few States have only one abandonment, while several others 
have more than 40. One State (Iowa) has as many as 53 lines slated for 
abandonment. Tne highest incidence of these abandonments occurs in the Mid- 
west and several States bordering the Great Lakes. 

In view of the close relationship between rail transport and domestic 
mineral shipping, there is a clear need for a minerals impact evaluation of 
the abandonment situation just detailed. Therefore, this study has been 
prepared to identify and evaluate projected impacts of potential large-scale 
rail line abandonments on U.S. nonfuel mineral industies. 



■ 5 

Underlined numbers in parentheses refer to items in the bibliography, 
"The ICC was given control over railroad abandonment by the Transportation 
Act of 1920. 



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Related Studies 

Previous abandonment impact studies primarily have been concerned with 
economic effects on communities in the vicinity of abandonment or with the 
effects on agricultural shippers, particularly those in farming regions 
that have experienced numerous abandonments in recent years. Additionally, 
these studies, unlike this study, focused on relatively few rail lines or on 
presumably uneconomic lines with abandonment potential, rather than analyzing 
on a national scale all lines actually slated for abandonment. A bibliography 
of rail abandonment impact studies is presented in this report. 

Attention has been given to some mineral industries in a few abandonment 
impact studies. These studies suggest that adverse effects can occur from 
abandonment. 4 In 1975, for example, part of a University of Illinois 
study (9_) indicated that the abandonment of two rail lines in Nevada had 
resulted in higher mining costs and apparently deterred the revival of some 
mining operations. Also, a study for the U.S. Department of Transportation 
in 1977 indicated potential increases in mineral transport costs if apparently 
uneconomic rail lines were abandoned (24). A study for the Bureau of Mines 
alluded to instances of abandonment of rail lines that served mines in various 
parts of the United States (25) . 

STUDY METHODOLOGY 

In this study, four principal sources of information were analyzed to 
determine the impact of rail abandonment: 

1. The Bureau of Mines Mineral Industry Location System (MILS) was 
utilized to identify and locate mines , mineral deposits , and mineral pro- 
cessing facilities in the vicinity of the 688 prospective rail line 
abandonments discussed earlier. 

2. Freight commodity data for over 100 rail line abandonment application 
cases pending before the ICC were examined to determine current mineral 
tonnages hauled on the lines. Approximately 100 additional abandonment 
applications to the ICC were surveyed to determine the pace of abandonment 
and its predominant regional pattern. 



An excellent example of rail abandonment and its effect on mineral 

developement involved the Bureau of Mines and the recent closure of a 
16-mile span of the Maine Central Railroad in Franklin County, Maine. In 
this case, the Bureau provided supporting evidence to the State of Maine 
for its petition before the U.S. Court of Appeals to reverse an ICC 
abandonment authorization. The Bureau's State Liaison Office indicated 
that the subject rail line could play a key role in several anticipated 
local mining operations (garnet, limestone, and sand production). However, 
the Court declined to review the case and abandonment ensued in late 1978. 



3. The Bureau's State Mineral Profile publications were used to 
supplement MILS data. 

4. Previous studies of rail abandonment effects on commerce and industry 
were examined for indicators of possible impacts on mineral industries. 

Analysis of these sources proceeded primarily in two ways: First, 
commodity tonnage and origin-destination data in the abandonment application 
records held by the ICC were used to identify the impact of immenent applications . 
(Decisions on most abandonment applications are made within 60 days and rarely 
take longer than 1 year.) The details and results of this analysis are shown 
in the following section. Second, the MILS data base was statistically 
correlated with the location of the 688 prospective abandonments announced 
by the ICC in an attempt to identify the impact of the abandonments in the 
absence of freight data for these lines. This approach also tends to show 
longer range impacts because , at the present rate of abandonment , the 688 
abandonments probably would not be completed until well after 1981. A more 
detailed explanation of the methodology used in this approach follows . 

All of the 688 prospective abandonments were plotted on 1:500 ,000-scale 
State maps published by the U.S. Geological Survey. Three types of abandon- 
ment were plotted on each State map: (1) more than 130 lines for which 
abandonment applications were currently pending before the ICC, (2) approximately 
350 lines that ICC expected rail companies would seek to abandon by mid-1981, 
and (3) more than 210 lines under study that the ICC believed would be 
subject to future abandonment attempts . 

The areas that presumably were most likely to be affected by the aban- 
donment were then plotted on the State maps. These "impact areas" were 
graphically defined by drawing a boundary around each prospective abandonment 
to enclose all points that were closer to the abandonment line than to any 
remaining rail lines . Thus , the boundary for each impact area was usually 
drawn equidistant between the abandoned line and nearest remaining rail lines 
(see fig. 1). Where it was observed that impassable terrain features 
(rivers, mountain ranges, etc.) without transport routes intervened between 
the lines slated for abandonment and other rail lines, the boundary for the 
impact area was drawn along these features rather than equidistant between 
the lines. On the other hand, the boundaries were drawn irrespective of 
roads and waterways because it was determined that the pattern of alternative 
transport routes did not appreciably affect the overall impact area size 
or configuration. 5 In some cases, adjacent impact areas for two or more 
prospective abandonments in close proximity would coalesce into a single 
larger impact area. 

The impact area concept is significant because any potential freight 
originating within the impact area would require longer movement by 
alternative transport modes if abandonment occurred. Except for relatively 

5 Statistical testing of a random sample of impact areas indicated that highway 
routes crossing the impact area boundary did not significantly change the 
total size of the impact areas. 




FIGURE 1. - Schematic diagram showing procedure for 
mapping abandonment impact areas. 

the impact areas was then statistically tested as 
section. 



few areas where waterways 
are available, it can be 
assumed that most of the 
additional movement would 
be by truck, which is 
likely to be more costly 
and less energy efficient. 
Thus , the impact area is 
the most likely place 
where abandonment would 
increase the costs of 
mineral shipping. In 
addition, heavier truck 
use would probably lead 
to more rapid deteriora- 
tion of roadways in the 
area . 

After the abandonments 
and their impact areas were 
plotted, map overlays 
showing the location of all 
MILS mineral-related sites 
were placed over their 
respective State maps to 
identify the sites located 
within each impact area. 
A total of over 30,000 MILS 
mineral location points 
were on the overlays used 
in this procedure . 6 A 
tabulation of the number 
and types of MILS sites in 
described in the following 



Finally, a few caveats concerning this impact area methodology should 
be noted: First, the methodology is based on the premise that impact is 
measured solely as an enumeration of MILS sites. Obviously, the number of 
mineral-related sites alone does not fully measure impact. In terms of 
employment, production, or other such factors, one site can be more impor- 
tant than several. Thus, a large number of sites in an impact area should 
be viewed as an indicator, not conclusive evidence, of major impacts. 
Second, the enumeration of MILS sites was based on the most current listing 
available as of January 1979. Since that time, the MILS data base has 
continued to grow with hundreds of new sites being added each month. Analysis 



6 These points are known as "clusters" in the MILS because, for ease of 
mapping, they represent groups of several closely located mineral 
properties. In all, these clusters represented more than 85,000 mineral 
properties at the time this study was done. 



of new additions to MILS could, of course, alter the conclusions reached with 
the 1979 base. In addition, it must be noted that the MILS data base is in 
different stages of completion for various parts of the country. Thus, 
interregional variations in the number of listed MILS sites reflects dif- 
ferences in data input as well as actual on-the-ground variations in site 
density. Nevertheless, despite these qualifying remarks, the impact area 
methodology outlined above is a viable alternative in lieu of freight tonnage 
data not available for the prospective abandonments announced by the ICC. 

DATA DESCRIPTION AND ANALYSIS 

Near-Term Impact Data 

A survey was made of more than 200 rail line abandonment applications, 
including freight records and court proceedings, pending before the ICC between 
June 1978 and January 1980. The survey was conducted, to determine where rail 
lines were facing imminent abandonment, the pace of abandonment, and what 
mineral commodities were carried by the lines being abandoned. Approximately 
half of the surveyed lines were sampled to identify the commodities carried, 
while the remaining 100 lines were analyzed to identify the rate and locale 
of abandonment. 

Table 2 shows the type of quantity of nonfuel mineral materials carried 
by rail lines pending ICC abandonment approval (or disapproval) as of 
June 1978. The data were drawn from a 50-percent random sample of the 104 
abandonment applications pending at that time. The applications from which 
the sample was drawn represented the lines of 39 railroad companies in 30 
States, mostly in the Midwest and along the Great Lakes. 

TABLE 2. - Raw and processed mineral materials carried by 52 
rail lines pending abandonment as of 1978 1 



Categorv of mineral materials carried Percent of total tonnage carried 
Fertilizers (lime, limestone, phosphate 

rock, potash, etc.) 11.8 

Nonmetallics (cement, clay, glass, gravel, 

ores, salt, sand, and stone) 6.9 

Primary and fabricated metals 1.6 

Other (metallic ores, scrap, brick, etc.)... ._3 

Total ■■. 20.6 

x Based on a 50- percent random sample of 104 rail lines. 
All freight carried by the 52 rail lines totaled approximately 4.5 million 
short tons annually during 1975-77. 

Source: Rail abandonment application records; Documents Library, Interstate 
Commerce Commission. 

As shown in table 2, raw and processed mineral materials comprised 
slightly over 20 percent of the tonnage moved on lines proposed for abandon- 
ment. However, it should be noted that all of the mineral-related tonnage 
equates to an average of less than 18,000 short tons for each line, or only 



2 



about 200 rail cars per line each year. Most of the mineral tonnage was 
accounted for by fertilizer shipments. This is not surprising because most 
of the surveyed lines facing abandonment are in the agriculturally-oriented 
regions of the country. 

Other nonmetallic minerals formed the second largest category of mineral 
freight moved over the lines slated for abandonment. The traffic consisted 
primarily of raw mineral commoditites such as sand, gravel, clay, and stone, 
which were hauled relatively short distances. 

By January 1980 , over 90 percent of the sampled abandonment cases had 
been resolved by ICC; almost all were decided in favor of abandonment. 
However, approximately 100 new applications were pending. These applications 
were studied to further identify the pace and locale of abandonment. Again, 
a large portion of the new applications were for rail lines in the Midwest 
and other agricultural areas nearby. Interviews with ICC personnel 7 con- 
cerning the rate and geographic pattern of abandonment confirmed that the 
emphasis on these farming areas probably would continue through the early 
1980's. Thus, mineral fertilizers are expected to continue as a prominent 
part of the shipping that will be disrupted by abandonment over the next 
few years . 

In addition to fertilizer materials, our review of abandonment records 
found scattered, localized instances of hardships for mineral shippers. 
Periodically, testimony in abandonment proceedings claimed that small, local 
mineral-related facilities such as a brick refractory or clay products plant 
would be forced to close if abandonment took place. However, there was 
nothing in the records that revealed recurring instances of problems for 
shippers of a particular category of minerals other than fertilizers . In the 
case of fertilizers , total tonnage involved was relatively small and 
distributed over many rail lines. 

In summary, the survey of ICC data and abandonment records indicate that 
abandonments are not likely to require a major shift in transport modes for 
nonfuel minerals in the near future. This observation assumes that abandon- 
ment proceedings will not be accelerated beyond their present pace and that 
there will not be a major shift in the current regional pattern of 
abandonment . 

Long-Range Impact Data and Statistical Tests 

Long-Range Impact Data 

Estimates of longer range abandonment impacts are derived primarily from 
data shown in tables 1 and 3, and the list of impact-area facilities and/or 
properties. Statistical analysis correlating this data is described in the 
following subsection. 



7 Office of Proceedings, January 1980. 






TABLE 3 . - MILS mineral sites within abandonment impact areas , by State 1 



State 


MILS points 
in impact areas 


State 


MILS points 
in impact areas 




12 



2 

126 

9 

13 



17 

6 

125 

63 

33 

12 

3 

10 

6 

53 

19 

32 

114 

9 

7 

110 


North Dakota 


76 




63 


Arkansas 


7 






3 




57 

42 

7 


Florida 




22 




Ohio 


46 


Idaho 




6 






17 






18 




South Dakota 


20 


Kansas 


197 






35 




8 







12 




19 


Michigan 




254 






37 






246 




Total 2 


1,973 



1 The definition and derivation of abandonment impact areas are discussed 

under Study Methodology. 

2 Total accounts for 6 percent of all MILS points in these States. 

Table 3 shows the number of MILS minerals-related point locations falling 
within the impact areas (as previously described under Study Methodology) of 
each State. As shown in the table, nearly 2,000 MILS points were identified 
in the impact areas of the 688 abandonment-prone rail lines announced by the 
ICC. These points represented an estimated 5,800 mineral properties, equal to 
7 percent of the total MILS data base. Well over half of the points (1,123) 
represented inactive sites composed of undeveloped prospects and closed mines 
and plants, 615 represented active sites of producing mines and operating 
plants, and the remaining 235 points represented both active and inactive sites 
The predominance of inactive sites may portend greatly reduced opportunities 
to develop new prospects or reopen closed facilities. 



10 



The following list shows the varieties of minerals as well as mining and 
processing activities that are located at the MILS points in the impact areas: 1 



Mineral materials' 



Antimony 

Asbestos 

Barite 

Bauxite 

Bentonite 

Beryllium 

Calcium 

Cement 

Clay 

Columbium 

Copper 

Corundum 

Diatomite 

Feldspar 

Fluorine 

Gem stones 

Germanium 

Glass 

Gold 

Granite 

Gravel 

Gypsum 

Iridium 

Iron ore 

Kaolin 

Kyanite 

Lead ore 

Lime 

Limestone 

Magnesium 



Magnetite 

Manganese 

Marble 

Molybdenum 

Mica schist 

Nickel 

Pegmatite 

Perlite 

Phosphate rock 

Phosphorus 

Platimum 

Pyrite 

Osmium 

Quartz 

Rare- earth minerals 

Salt 

Sand 

Shale 

Silica 

Silver 

Slate 

Sodium 

Sulfur 

Taconite 

Talc 

Thorium 

Titanium 

Tungsten 

Vermiculite 

Zinc 

Zirconium 



Mineral facilities and/or properties' 

Abrasives 

Brick production plants 

Brine production plants 

Clay products plants 

Crushing mills 

Fiberglass plants 

Forgings plants 

Glass-producing plants 

Grinding mills 

Metal works 

Milling plants 

Mines 

Mineral deposits 

Mineral pits 

Mineral placers 

Mineral prospects 

Pelletizing plants 

Quarries 

Refractory plants 



1 The definition and derivation of abandonment impact areas are discussed 
under Study Methodology „ 
As identified in MILS data base. 

Sixty-one mineral materials and 19 types of facilities , operations , or 
properties have been identified at these points , 

In the impact areas, nonmetallic mineral sites greatly outnumbered 
metallic mineral sites. By far the most frequently encountered nonmetallic 
site types were sand, gravel, and limestone quarries with the usual auxiliary 
preparation mills and plants. These quarries were about evenly divided between 
active and inactive statuses. Numerous prospects, both metallic and non- 
metallic, were found in impact areas throughout 18 States, primarily in the 
East. Iron, lead, and zinc prospects (both developed and undeveloped) and 
abandoned mines were among the most frequently encountered metallic mineral 
sites contained in the Impact areas. 



11 



Statistical Tests 

In view of the great number and variety of MILS sites located in the 
abandonment impact areas , the data presented in tables 1 and 3 were submitted 
to various, statistical tests to determine what correlation, if any, existed 
between the location of prospective rail abandonments and the occurrence of 
MILS sites throughout the United States. A strong correlation would indicate 
that the occurrence of MILS sites in the impact areas was not due to chance 
but was the result of an unusually high frequency of abandonment in mining 
and mineral-processing areas. Details of the statistical tests are presented 
in the appendix. 

Testing began with simple regression analysis. In the initial three 
simple regression analyses, the dependent variable was the total number of 
MILS points in each State, and the independent variables were those of 
abandonment mileage , number of abandonment lines , and percent of track net- 
work to be abandoned in each State. These tests each yielded a coefficient 
of determination (R 2 ) of less then 0.002, indicating virtually no correlation. 
However, these initial tests did not consider a key factor — the geographic 
distribution of abandonment lines and MLS location points within each State. 
The intrastate distribution of abandonment -prone rail lines and MILS points 
determines whether or not they will coincide geographically, regardless of 
their total numbers in each States. 

The relationship between abandonment lines and MILS points within each 
State was examined by measuring the correlation between MILS points in the 
impact areas of each State and various rail line abandonment parameters. 
Three simple regression analyses were performed using the total number of 
MILS points in the impact areas of each State as the dependent variable and 
the following parameters as the independent variables: (1) number of rail 
lines to be abandoned in each State, (2) track mileage to be abandoned in 
each State, and (3) percent of total State track network to be abandoned. 
The R values for the regression analyses of these variables were as follows: 





Independent variable 


R 2 va lue 


1 




0.15 


9 




.28 


3. . 




.18 



Another possible hypothesis is that the number of MILS points within 
impact areas also could be a function of the total number of MILS points in 
each State. Therefore, the number of points in the impact areas was tested 
for correlation with the total number of MILS points in each State. The test 
yielded an R 2 of 0.32, which is higher than the R 2 values achieved with the 
three rail abandonment variables noted above. 

After completing the tests just described, the independent variables 
that yielded the highest R 2 values were combined in multiple regression 
analysis to examine further the coincidence of MILS points and impact areas. 
(Combinations were used only if the degree of association between the 
independent variables was an R 2 of less than 0.01.) Thus, the number of 



12 



impact area points for each State was used as the dependent variable and 
correlated to the following combinations of independent variables: (1) aban- 
donment mileage in each respective State plus total number of MILS points 
in the State, and (2) percent of State track network to be abandoned plus 
total number of MILS points in the State. The coefficient of multiple 
determination (R 2 ) between the dependent variable and these two sets of 
independent variables was shown to be 0.59 and 0.65, respectively. 8 Although 
these were the two highest values attained in regression analysis, they do 
not indicate a particularly high degree of correlation between MILS points 
and abandonment impact areas. Furthermore, a substantial part of the R 2 
values are due to the correlation between total MILS points and impact area 
points rather that between MILS points and the track abandonment parameters. 

In summary, the R 2 values of all statistical tests utilized in this 
study were not high enough to indicate a significant correlation between 
the prospective rail abandonments and the location of mineral properties 
and facilities. Based on these tests, there is little reason to believe that 
any geographic coincidence of these variables is more than a random occurrence 
Thus , the tests do not provide sufficient evidence to contend that the 
abandonments unduly impact on mining and mineral-processing areas. 

CONCLUSIONS 

Concurrent with the trend toward large-scale abandonment of U.S. rail 
lines , this study analyzed the potential impacts of abandonment on domestic 
mineral industries. The conclusions reached in this study are derived 
principally from the analysis of 200 rail line freight records, over 2,000 
mineral sites, and 700 prospective abandonments in 45 States. These 
conclusions are as follows: 

1. Raw and processed nonfuel minerals probably will comprise a large 
percentage of the traffic disrupted by the abandonment of rail lines in the 
next few years. However, the actual mineral tonnage involved will be small 
compared with total domestic mineral traffic and will be distributed over 
many lines. Most of the this mineral freight will be accounted for by 
fertilizer materials carried within agricultural regions and by relatively 
low-value minerals (rock, sand, gravel, etc.), which are normally moved 
short distances. Thus, local short-haul producers and/or shippers will be 
affected. 

2. Instances of hardship on some small mineral shippers already have 
resulted from abandonment. Moreover, adverse impacts on mineral producers 
that were important to their local economies were observed frequently enough 
to suggest a need for safeguards that would mitigate the effects of 
abandonment disruption. 

3. Although a great number and variety of mineral sites were identified 
in the abandonment impact areas , statistical analysis did not indicate a 

8 Computed T-values between the dependent variable and the independent 
variables ranged from 5.1 to 6.1. 



13 



strong coincidence of MILS mineral sites and prospective rail line aban- 
donments. Thus, the occurrence of MILS sites in the impact areas does not 
appear to be the result of abandonments focused on mining and mineral- 
processing areas. However, it should be noted that this conclusion is 
subject to the caveats described in the Study Methodology section. 

4. The predominance of inactive mineral prospects and closed mining 
facilities in many abandonment impact areas, principally in Western States, 
suggests that abandonment could significantly reduce the opportunity to 
develop new resources or reopen defunct mining operations in those areas. 

5. Despite the problems noted above, this study did not discern any 
long-term abandonment trends with national or broad regional dimensions 
that would require major shifts in transport modes for nonfuel minerals. 

This conclusion assumes no acceleration in the pace of abandonment proceedings 
and no major alteration in the current geographic pattern of abandonment. 



14 



BIBLIOGRAPHY 

1. Allen, B. J., and J. F. Due. The Effects of the Abandonment of Railway- 

Lines Upon the Communities Served--A Summary of the Studies. 
Transportation Res. Paper 8. College of Commerce and Business 
Administration, University of Illinois, Urbana -Champaign, 111. 
June 1975, 36 pp. 

2. Anderson, D. G., and F. D. Gaibler. Economic Effects of Abandoning 

Branch Rail lines. Farm, Ranch and Home Quarterly. Univ. Nebr. 
Inst. Agr. and Nat. Res., Lincoln, Nebr. pp. 20-22. 

3. Boston University Bureau of Business. The Economic Impact of the 

Discontinuance of the Rutland Railway. Studies on the Economic Impact 
of Railway Abandonment and Service Discontinuance. U.S. Department 
of Commerce, Transportation Research, Washington, D.C. , 1965, 83 pp. 

4. Buchanan, S., B. L. Cole, A. R. Fergison, N. H. Jones, V. Habib, and 

B. Slavsky. Community Impacts of Abandonment of Railroad Service. 
United States Railway Association, Washington, D.C, June 1975, 192 pp. 

5. Bunker, A. R. Impact of Rail Line Abandonment on Agriculture Production 

and Associated Grain Marketing and Fertilizer Supply Firms. Ph. D. 
Thesis, Univ. 111., Urbana -Champaign, 111., 1975, 186 pp. 

6. Colucci, R. Summary Report on the Impact of Loss of Rail Freight Services 

on Local Users. New York State Department of Transportation, New York 
State Railroad Task Force, April 1974, 60 pp. 

7. CONSAD Research Corp. Analysis of Community Impacts Resulting From 

the Loss of Rail Service. United States Railway Association, 
Washington, D.C, February 1975, 462 pp. 

8. Due, J. F. A Case Study of the Effects of the Abandonment of a Railway 

Line--Sherman and Wasco Counties, Oregon. Transportation Res. Paper 5. 
College of Commerce and Business Administration, University of 
Illinois, Urbana -Champaign, 111., September 1974, 79 pp. 

9. . Long Term Impact of Abandonment of Railway Lines. Transportation 

Research Paper 7. College of Commerce and Business Administration, 
University of Illinois, Urbana -Champaign, 111., June 1975, 42 pp. 

10. Gaibler, F. D. Economic Impact of Abandonment on Country Grain Elevators 

in South-Central Nebraska. M. S. Thesis, Univ. Nebr., Lincoln, Nebr., 
1974, 110 pp. 

11. Herman, E. E., D. C. Nelson, and T. K. Ostenson. Impact of Railroad 

Branch Line Abandonment on the North Dakota Tax Structure (Part 1). 
Upper Great Lakes Transportation Institute, N. Dak. State Univ. 
Fargo, N. Dak., Rept. 8, June 1969, 30 pp. 



15 



12. Humphrey T. J. Framework for Predicting External Impacts of Railroad 

Abandonments. Department of Civil Engineering, Transportation 
Systems Division. Massachusetts Institute of Technology, Cambridge, 
Mass. , 1975, 70 pp. 

13. Hyman W. A., and J. W. Fuller. Energy and Environmental Effects of 

Railroad Abandonment. Transportation Research Board, Washington, D.C., 
January 1976, 18 pp. 

14. Jack Faucett Associates, Inc. Potential Economic Impact of Termination 

of Rail Service to Twelve Selected Communities. U.S. Department of 
Transportation, Washington, D.C., December 1973, 132 pp. 

15. Janski, R. G. The Economics, Social and Energy Impacts of North Dakota 

Rail Branchline Abandonments. M. S. Thesis, N. Dak. State Univ. 
Agr. and Appl. Sci. , Fargo, N. Dak., July 1975, 101 pp. 

16. Minnem, G. M. Effects of Railroad Abandonment on Grain Producers and 

Grain Elevator Supply Areas in North Central Kansas. Ph. D. Thesis, 
Kans . State Univ. Manhattan, Kans . , 1974, 559 pp. 

17. Jolissaint, C. H. , D. P. Lijesen, P. W. Merkens , and J. Rossing. 

The Railroad Reorganization Act and Its Impacts on Economic Development, 
Appalachian Regional Commission, Washington, D.C. October 1974, 95 pp. 

18. Office for Planning and Programming, Iowa Commerce Commission and Iowa 

State Highway Commission. Economic Impacts of Railroad Abandonment 
in Iowa: A Case Study. March 1973, 49 pp. 

19. Purnell, L. 0. A Methodology for Evaluating the Impact of Railroad 

Abandonment on Rural Highways . Joint Highway Research Project JHRP 
76-4, Engineering Experiment Station, Purdue University and Indiana 
State Highway Commission, West Lafayette, Ind., January 1976, 217 pp. 

20. Railroad Planning Management Committee, Minnesota State Planning Agency. 

Minnesota Railroad Line Abandonment Study-A Report to the Legislature. 
St. Paul, Minn., January 1976, 40 pp. 

21. Rail Service Planning Office. Guide for Evaluating the Community Impact 

of Rail Service Discontinuance. Interstate Commerce Commission, 
Washington, D.C, January 1975, 87 pp. 

22. U.S. Department of Transportation, Office of Environmental Affairs. 

Availability and Use of Abandoned Railroad Rights -of -Way . Washington, 
D.C. , June 1977, 73 pp. 

23. U.S. Department of Transportation, Office of the Secretary. Railroad 

Abandonment and Alternatives: A Report on Effects Outside the 
Northeast Region. Washington, D.C, May 1976, 115 pp. 



16 



24. Weinblatt , W. , and D. Matzzie. Effects of Railroad Abandonment on the 

Modal Distribution of Traffic and on Related Costs. U.S. Department 
of Transportation, Washington, D.C. September 1977, 290 pp. 

25. . Forecast of Developments in Domestic Minerals Transport. 

BuMines Open File Report 4-78, 1977, 228 pp; available for consulta- 
tion at the National Library of Natural Resources, U.S. Department 
of the Interior, Washington, D.C; and from the National Technical 
Information Service, Springfield, Va. , PB 276 560. 



17 



APPENDIX.— DETAILS OF STATISTICAL TESTS 

Simple Linear Regressions 1 

When Y = number of MILS cluster points in the impact areas of each State , 
and X = percent of railroad track abandoned in each State (45 States), 

then the regression equation is Y = 17 + 2.77 X, 

R 2 (coefficent of determination) is 0.18, 
and computed T-value is 3.14. 



When Y = number of MILS cluster points in the impact areas of each State, 
and X = track mileage to be abandoned in each State (45 States), 



then the regression equation is Y = 13 +8.27 X 

R 2 (coefficient of determ 
and computed T-value is 4.13. 



R 2 (coefficient of determination) is 0.28, 



When Y = number of MILS cluster points in the impact areas of each State, 
and X = number of rail lines to be abandoned in each State (45 States) , 

then the regression equation is Y = 15 + 1.87 X, 

R 2 (coefficient of determination) is 0.15, 
and computed T-value is 2.77 



When Y = number of MILS cluster points in the impact areas of each State, 
and X = total number of MILS sites in each State (42 States), 



then the regression equation is Y = 12 + 4.76 X, 

R 2 (coefficient of determ: 
and computed T-value is 4.42. 



R 2 (coefficient of determination) is 0.32, 



When Y = total number of MILS cluster points in each State, 

and X = track mileage to be abandoned in each State (42 States), 

then the regression equation is Y = 403 - 0.02 X, 
R 2 (coefficient of determination) is 0.0009, 
and computed T-value = -0.19. 



1 With Y as the dependent variable and X as the independent variable. 



18 



When Y = total number of MILS cluster points in each State, 

and X = percent of railroad track to be abandoned in each State (42 States) 

then the regression equation in Y = 695 + 3.95 X, 

R 2 (coefficient of determination) is 0.002, 
and computed T-value is 0.26. 



When Y = total number of MILS cluster points in each State, 

and X = number of rail lines to be abandoned in each State (42 States) 



then the regression equation is Y = 757 - 1.81 X, 
R 2 (coefficient of determination) is 0.0008, 
and computed T-value is 0.18. 

Multiple Regression Analysis 2 

When Y = number of MILS cluster points in the impact areas of each State, 

X x = total number of -MILS cluster points in each State, 
and Xg = percent of railroad track to be abandoned in each State (42 States), 

then the regression equation is Y = -25 +0.05 X x + 4.6 Xg , 

R 2 (coefficient of multiple determination) is 0.65, 

computed T-value for X x is 5.7, 
and computed T-value for Xg is 6.1. 

When Y = number of MILS cluster points in the impact areas of each State, 

X 1 = total number of MILS cluster points in each State, 
and Xg = track mileage to be abandoned in each State (42 States), 

then the regression equation is Y = 21.5 + 0.05 X x + 0.08 Xg , 

R 2 (coefficient of multiple determination) is 0.59, 

computed T-value for X x is 5.6, 
and computed T-value for Xg is 5.1. 



'With Y as the dependent variable and X x and Xg as the independent variables 



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